The global AI In Asset Management market size is expected to be worth around US$ 13.44 billion by 2028, according to a new report by Vision Research Reports.
The global AI In Asset Management market size was valued at US$ 990.5 million in 2020 and is anticipated to grow at a CAGR of 37.2% during forecast period 2021 to 2028.
Artificial intelligence in asset management refers to the automation of IT assets lifecycles with intuitive workflows and making informed decisions about asset vendors and capacity. Asset and wealth management firms are exploring potential artificial intelligence-based solutions to improve their investment decisions and extract insights out of their historical data. The current landscape of (AI) applications in asset and investment management includes the management of digital assets and physical assets and investment advisory consumer applications. For instance, The Vanguard Group, Inc., a U.S.-based investment firm, offers the PAS (Personal Advisor Services), which runs on automated algorithms and can potentially prompt customers with investments-related advisories with insights from human advisors.
The COVID-19 outbreak has created significant uncertainties and challenges for the WAM industry. However, this crisis may accelerate certain activities related to the speed of digital transformation and automation as some markets have shown high acceptance towards digital or virtual approaches related to client interaction and distribution. Moreover, key players are leveraging AI and technologies to improve resilience and enhance productivity. For instance, in April 2020, Exabel, a Norway-based FinTech company that provides an AI platform for active asset managers, announced its partnership with 1010data, Inc., a U.S.-based data provider to the consumer goods, retail, and BFSI industries. Under the agreement, both the companies are working on building COVID-19 impact dashboards, which will derive the information from multiple sets of live debit and credit transaction data. This information is anticipated to provide investors real-time insights into how this pandemic impact consumer spending in grocery and general merchandise, retail, and travel industries across U.S. Furthermore, omnichannel and ecosystem strategies are expected to become embedded within the capital markets sector to maintain restricted social distancing and travel in place.
Machine learning led the market and accounted for more than 65.01% share of the global revenue in 2019. This is attributed to increasing process automation in manufacturing industries. (ML) reflects the natural evolution of technology as machines are capable of sorting through large datasets and extract information by identifying patterns and outliers. ML is being employed in the asset management systems to increase the accuracy and efficiency of operational workflow, improve the customer experience, and enhance the system performance.
On-premises led the market and accounted for 60.2% share of the global revenue in 2019. This is attributed to the security and privacy provided by the on-premises solutions in asset management. Moreover, on-premise solutions use edge analytics that reduces the bandwidth requirement. Integrating these solutions on-premise brings higher speed and more reliability in the results.
The portfolio optimization segment led the market and accounted for 25.2% share of the global revenue in 2019. This is attributed to the high adoption of machine learning algorithms in asset management to facilitate portfolio management decisions. Portfolio optimization includes several use-cases, such as portfolio construction and optimization, predictive forecasting of long-term price analysis, and development of strategies for risks associated with investments. A prototype for portfolio optimization in the investment process is built based on stock selection, portfolio management process, and asset allocation optimization.
The BFSI segment led the market and accounted for more than 20.01% share of the global revenue in 2019. This is attributed to the rapid adoption of AI in asset management systems in the financial services and banking sector. There are several applications of AI in financial services, including alpha generation and stewardship in asset management, risk management, fraud detection, relationship manager augmentation, and algorithmic trading. For instance, BlackRock, Inc., an American investment management organization, offers an asset management solution, called Future Advisor that digitizes the wealth management process for financial institutions and their advisors to serve clients in a scalable way.
North America dominated the market and accounted for over 50.01% share of global revenue in 2019. This is attributed to favorable government initiatives to encourage the adoption of artificial intelligence (AI) across various industries. For instance, in February 2019, U.S. President Donald J. Trump launched the American AI Initiative as the nation’s strategy for promoting leadership in. As part of this initiative, Federal agencies have fostered public trust in AI-based systems by establishing guidelines for its development and real-life implementation across different types of industrial sectors.
Amazon Web Services, Inc.
Charles Schwab & Co., Inc
International Business Machines Corporation
Next IT Corp.
Natural Language Processing (NLP)
Deployment Mode Outlook
Risk & Compliance
Retail & E-commerce
Energy & Utilities
Media & Entertainment
Middle East and Africa (MEA)
The AI In Asset Management market research report covers definition, classification, product classification, product application, development trend, product technology, competitive landscape, industrial chain structure, industry overview, national policy and planning analysis of the industry, the latest dynamic analysis, etc., and also includes major. The study includes drivers and restraints of the global market. It covers the impact of these drivers and restraints on the demand during the forecast period. The report also highlights opportunities in the market at the global level.
The report provides size (in terms of volume and value) of AI In Asset Management market for the base year 2020 and the forecast between 2021 and 2028. Market numbers have been estimated based on form and application. Market size and forecast for each application segment have been provided for the global and regional market.
This report focuses on the global AI In Asset Management market status, future forecast, growth opportunity, key market and key players. The study objectives are to present the AI In Asset Management market development in United States, Europe and China.
It is pertinent to consider that in a volatile global economy, we haven’t just conducted AI In Asset Management market forecasts in terms of CAGR, but also studied the market based on key parameters, including Year-on-Year (Y-o-Y) growth, to comprehend the certainty of the market and to find and present the lucrative opportunities in market.
In terms of production side, this report researches the AI In Asset Management capacity, production, value, ex-factory price, growth rate, market share for major manufacturers, regions (or countries) and type.
In terms of consumption side, this report focuses on the consumption of AI In Asset Management by regions (countries) and application.
Buyers of the report will have access to verified market figures, including global market size in terms of revenue and volume. As part of production analysis, the authors of the report have provided reliable estimations and calculations for global revenue and volume by Type segment of the global AI In Asset Management market. These figures have been provided in terms of both revenue and volume for the period 2017 to 2028. Additionally, the report provides accurate figures for production by region in terms of revenue as well as volume for the same period. The report also includes production capacity statistics for the same period.
With regard to production bases and technologies, the research in this report covers the production time, base distribution, technical parameters, research and development trends, technology sources, and sources of raw materials of major AI In Asset Management market companies.
Regarding the analysis of the industry chain, the research of this report covers the raw materials and equipment of AI In Asset Management market upstream, downstream customers, marketing channels, industry development trends and investment strategy recommendations. The more specific analysis also includes the main application areas of market and consumption, major regions and Consumption, major Chinese producers, distributors, raw material suppliers, equipment providers and their contact information, industry chain relationship analysis.
The research in this report also includes product parameters, production process, cost structure, and data information classified by region, technology and application. Finally, the paper model new project SWOT analysis and investment feasibility study of the case model.
Overall, this is an in-depth research report specifically for the AI In Asset Management industry. The research center uses an objective and fair way to conduct an in-depth analysis of the development trend of the industry, providing support and evidence for customer competition analysis, development planning, and investment decision-making. In the course of operation, the project has received support and assistance from technicians and marketing personnel in various links of the industry chain.
The AI In Asset Management market competitive landscape provides details by competitor. Details included are company overview, company financials, revenue generated, market potential, investment in research and development, new market initiatives, global presence, production sites and facilities, production capacities, company strengths and weaknesses, product launch, product width and breadth, application dominance. The above data points provided are only related to the companies’ focus related to AI In Asset Management market.
Prominent players in the market are predicted to face tough competition from the new entrants. However, some of the key players are targeting to acquire the startup companies in order to maintain their dominance in the global market. For a detailed analysis of key companies, their strengths, weaknesses, threats, and opportunities are measured in the report by using industry-standard tools such as the SWOT analysis. Regional coverage of key companies is covered in the report to measure their dominance. Key manufacturers of AI In Asset Management market are focusing on introducing new products to meet the needs of the patrons. The feasibility of new products is also measured by using industry-standard tools.
Key companies are increasing their investments in research and development activities for the discovery of new products. There has also been a rise in the government funding for the introduction of new AI In Asset Management market. These factors have benefited the growth of the global market for AI In Asset Management. Going forward, key companies are predicted to benefit from the new product launches and the adoption of technological advancements. Technical advancements have benefited many industries and the global industry is not an exception.
New product launches and the expansion of already existing business are predicted to benefit the key players in maintaining their dominance in the global market for AI In Asset Management. The global market is segmented on the basis of region, application, en-users and product type. Based on region, the market is divided into North America, Europe, Asia-Pacific, Latin America and Middle East and Africa (MEA).
In this study, the years considered to estimate the market size of AI In Asset Management are as follows:
Reasons to Purchase this Report:
- Market segmentation analysis including qualitative and quantitative research incorporating the impact of economic and policy aspects
- Regional and country level analysis integrating the demand and supply forces that are influencing the growth of the market.
- Market value USD Million and volume Units Million data for each segment and sub-segment
- Competitive landscape involving the market share of major players, along with the new projects and strategies adopted by players in the past five years
- Comprehensive company profiles covering the product offerings, key financial information, recent developments, SWOT analysis, and strategies employed by the major market players
In-depth interviews and discussions were conducted with several key market participants and opinion leaders to compile the research report.
This research study involved the extensive usage of both primary and secondary data sources. The research process involved the study of various factors affecting the industry, including the government policy, market environment, competitive landscape, historical data, present trends in the market, technological innovation, upcoming technologies and the technical progress in related industry, and market risks, opportunities, market barriers and challenges. The following illustrative figure shows the market research methodology applied in this report.
Market Size Estimation
Top-down and bottom-up approaches are used to estimate and validate the global market size for company, regional division, product type and application (end users).
The market estimations in this report are based on the selling price (excluding any discounts provided by the manufacturer, distributor, wholesaler or traders). Market share analysis, assigned to each of the segments and regions are achieved through product utilization rate and average selling price.
Major manufacturers & their revenues, percentage splits, market shares, growth rates and breakdowns of the product markets are determined through secondary sources and verified through the primary sources.
All possible factors that influence the markets included in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data. The market size for top-level markets and sub-segments is normalized, and the effect of inflation, economic downturns, and regulatory & policy changes or others factors are accounted for in the market forecast. This data is combined and added with detailed inputs and analysis from Vision Research Reports and presented in this report.
Market Breakdown and Data Triangulation
After complete market engineering with calculations for market statistics; market size estimations; market forecasting; market breakdown; and data triangulation. Extensive primary research was conducted to gather information and verify and validate the critical numbers arrived at. In the complete market engineering process, both top-down and bottom-up approaches were extensively used, along with several data triangulation methods, to perform market estimation and market forecasting for the overall market segments and sub-segments listed in this report.
Secondary Sources occupies approximately 25% of data sources, such as press releases, annual reports, Non-Profit organizations, industry associations, governmental agencies and customs data, and so on. This research study includes secondary sources; directories; databases such as Bloomberg Business, Wind Info, Hoovers, Factiva (Dow Jones & Company), TRADING ECONOMICS, and avention; Investing News Network; statista; Federal Reserve Economic Data; annual reports; investor presentations; and SEC filings of companies.
In the primary research process, various sources from both the supply and demand sides were interviewed to obtain qualitative and quantitative information for this report. The primary sources from the supply side include product manufacturers (and their competitors), opinion leaders, industry experts, research institutions, distributors, dealer and traders, as well as the raw materials suppliers and producers, etc.
The primary sources from the demand side include industry experts such as business leaders, marketing and sales directors, technology and innovation directors, supply chain executive, end users (product buyers), and related key executives from various key companies and organizations operating in the global market.
The study objectives of this report are:
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